Journal
OPTIK
Volume 125, Issue 19, Pages 5803-5807Publisher
ELSEVIER GMBH
DOI: 10.1016/j.ijleo.2014.07.070
Keywords
Machine vision; CCD camera; Conveyor belt; Longitudinal rip; Ethernet
Categories
Funding
- key technologies R & D program of Tianjin, China [13ZCZDGX01000]
- National Natural Science Foundation of China (NSFC) [51274150]
- Natural Science Foundation of Tianjin, China [12JCZDJC27800]
- Tianjin City High School Science & Technology Fund Planning Project [20130708]
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Under the background that mining conveyor belts are prone to failure in operation, the on-line fault detection technique based on machine vision for conveyor belts is investigated. High-brightness linear light sources arranged to a vaulted shape provide light for a line-array CCD camera to capture high-quality belt images. A fast image segmentation algorithm is proposed to deal belt images on-line. The algorithm for detecting longitudinal rip and belt deviation which are serious threat to the mine safety production from binary belt images is presented. Then, an on-line visual belt inspection system is developed. The laboratory testing results testify the validity of the visual inspection system. (C) 2014 Elsevier GmbH. All rights reserved.
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